This comprehensive n8n workflow automates the process of creating, updating, and utilizing content embeddings from a WordPress website for enhanced AI-powered chat interactions. It involves fetching all posts and pages, filtering relevant content, generating text embeddings using OpenAI’s models, and storing these embeddings in a Supabase vector database. The workflow also includes periodic checks for modified content, ensuring that embeddings stay current. When visitors initiate a chat, the system retrieves relevant documents based on their query, processes them with a GPT-4 model, and responds with source-linked answers. Additionally, it manages historical data for efficient retrieval and maintains an up-to-date index of website content.
Automated WordPress Content Embedding and Chat Integration
Node Count | >20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chatTrigger, @n8n/n8n-nodes-langchain.documentDefaultDataLoader, @n8n/n8n-nodes-langchain.embeddingsOpenAi, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryPostgresChat, @n8n/n8n-nodes-langchain.textSplitterTokenSplitter, @n8n/n8n-nodes-langchain.vectorStoreSupabase, aggregate, filter, httpRequest, manualTrigger, markdown, merge, postgres, respondToWebhook, scheduleTrigger, set, splitInBatches, stickyNote, supabase, switch, wordpress |
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